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使用微梳的频率复用光学储层计算

Frequency-multiplexed optical reservoir computing using a microcomb.

作者信息

Cuevas Jonathan, Hu Yue, Shi Baoqi, Liu Junqiu, Minoshima Kaoru, Kuse Naoya

机构信息

Graduate School of Sciences and Technology for Innovation, Tokushima, Japan.

International Quantum Academy, Shenzhen, China.

出版信息

Nanophotonics. 2025 Aug 29;14(18):3063-3073. doi: 10.1515/nanoph-2025-0260. eCollection 2025 Sep.

DOI:10.1515/nanoph-2025-0260
PMID:40970238
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12442360/
Abstract

Optical reservoir computing (ORC) promises fast, energy-efficient temporal inference by harnessing the rich transient dynamics of photonic systems. Yet most ORC demonstrations still depend on fiber delay lines or camera-based spatial multiplexing, which caps the clock rate at a few tens of MSa/s and complicates monolithic integration. Here we introduce a frequency-multiplexed ORC whose nodes are the individual modes of a dissipative Kerr-soliton microcomb generated in a high- SiN microresonator. The input signal is encoded as a rapid detuning modulation of the pump laser, so the intracavity dynamics of the microcomb provide both the high-dimensional nonlinear mapping and tens of nanoseconds of memory, while output weighting is realized optically with standard microring arrays. Numerical modeling with 60 comb modes provides a normalized mean-square error (NMSE) of 0.015 on the Santa Fe chaotic time-series task at 50 MSa/s and more than a tenfold reduction in symbol-error rate for nonlinear equalization (NLEQ) at 100 MSa/s. A proof-of-concept experiment using 37 measured modes also confirms the concept on the Santa Fe chaotic time-series and NLEQ benchmarks. Because both the microcomb and weighting network are fabricated by a complementary metal-oxide semiconductor (CMOS)-compatible process, the architecture offers a clear path toward compact, energy-efficient photonic processors operating at greater than 1 GSa/s, directly addressing the scalability and speed challenges of nanophotonic ORC.

摘要

光学储层计算(ORC)有望通过利用光子系统丰富的瞬态动力学实现快速、节能的时间推理。然而,大多数ORC演示仍依赖于光纤延迟线或基于相机的空间复用,这将时钟速率限制在几十兆采样每秒,并使单片集成变得复杂。在此,我们介绍一种频率复用的ORC,其节点是在高硅氮微谐振器中产生的耗散克尔孤子微梳的各个模式。输入信号被编码为泵浦激光器的快速失谐调制,因此微梳的腔内动力学既提供了高维非线性映射,又提供了几十纳秒的记忆,而输出加权则通过标准微环阵列以光学方式实现。使用60个梳状模式的数值建模在50兆采样每秒的圣达菲混沌时间序列任务上提供了0.015的归一化均方误差(NMSE),并且在100兆采样每秒时非线性均衡(NLEQ)的符号错误率降低了十倍以上。一个使用37个测量模式的概念验证实验也在圣达菲混沌时间序列和NLEQ基准上证实了这一概念。由于微梳和加权网络都是通过互补金属氧化物半导体(CMOS)兼容工艺制造的,该架构为实现大于1吉采样每秒运行的紧凑、节能光子处理器提供了一条清晰的途径,直接解决了纳米光子ORC的可扩展性和速度挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/c9cc7362a03f/j_nanoph-2025-0260_fig_010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/1c6db155d27c/j_nanoph-2025-0260_fig_001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/d5d18e634f9e/j_nanoph-2025-0260_fig_002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/f6fd7e25613c/j_nanoph-2025-0260_fig_003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/80cd6c1fe8ba/j_nanoph-2025-0260_fig_004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/f6c0ddbb9fc6/j_nanoph-2025-0260_fig_005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/18e830ed7915/j_nanoph-2025-0260_fig_006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/f3cbb0c3ef41/j_nanoph-2025-0260_fig_007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/e79097bd6e6f/j_nanoph-2025-0260_fig_008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/35db40bd5d5e/j_nanoph-2025-0260_fig_009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/c9cc7362a03f/j_nanoph-2025-0260_fig_010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/1c6db155d27c/j_nanoph-2025-0260_fig_001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/d5d18e634f9e/j_nanoph-2025-0260_fig_002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/f6fd7e25613c/j_nanoph-2025-0260_fig_003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/80cd6c1fe8ba/j_nanoph-2025-0260_fig_004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/f6c0ddbb9fc6/j_nanoph-2025-0260_fig_005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/18e830ed7915/j_nanoph-2025-0260_fig_006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/f3cbb0c3ef41/j_nanoph-2025-0260_fig_007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/e79097bd6e6f/j_nanoph-2025-0260_fig_008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/35db40bd5d5e/j_nanoph-2025-0260_fig_009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e321/12442360/c9cc7362a03f/j_nanoph-2025-0260_fig_010.jpg

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